| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.75 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 76.29% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1476 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "very" | | 1 | "softly" | | 2 | "sweetly" | | 3 | "gently" | | 4 | "really" | | 5 | "slowly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 66.12% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1476 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "glinting" | | 1 | "measured" | | 2 | "streaming" | | 3 | "footsteps" | | 4 | "echoed" | | 5 | "sanctuary" | | 6 | "flickered" | | 7 | "lilt" | | 8 | "grave" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 101 | | matches | (empty) | |
| 86.28% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 101 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 66 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1490 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 1 | | matches | | 0 | "Camden Town, it said, though they were a mile and a half from Camden." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 1296 | | uniqueNames | 24 | | maxNameDensity | 0.85 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 2 | | Quinn | 11 | | Brewer | 1 | | Street | 3 | | Tomás | 1 | | Herrera | 9 | | Soho | 1 | | London | 2 | | Saint | 1 | | Christopher | 1 | | Raven | 1 | | Nest | 2 | | Morris | 5 | | Christmas | 1 | | Berwick | 2 | | Underground | 1 | | Town | 1 | | Camden | 2 | | Tube | 1 | | Victorian | 1 | | Veil | 1 | | Market | 1 | | Sevillian | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" |
| | places | | 0 | "Brewer" | | 1 | "Street" | | 2 | "Soho" | | 3 | "London" | | 4 | "Raven" | | 5 | "Berwick" | | 6 | "Town" | | 7 | "Camden" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1490 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 42.57 | | std | 33.87 | | cv | 0.796 | | sampleLengths | | 0 | 17 | | 1 | 42 | | 2 | 51 | | 3 | 137 | | 4 | 10 | | 5 | 11 | | 6 | 50 | | 7 | 76 | | 8 | 72 | | 9 | 25 | | 10 | 7 | | 11 | 68 | | 12 | 46 | | 13 | 32 | | 14 | 54 | | 15 | 3 | | 16 | 89 | | 17 | 30 | | 18 | 11 | | 19 | 66 | | 20 | 11 | | 21 | 108 | | 22 | 32 | | 23 | 52 | | 24 | 41 | | 25 | 22 | | 26 | 25 | | 27 | 70 | | 28 | 23 | | 29 | 6 | | 30 | 125 | | 31 | 42 | | 32 | 8 | | 33 | 24 | | 34 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 101 | | matches | | |
| 46.39% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 217 | | matches | | 0 | "was running" | | 1 | "was still moving" | | 2 | "was weighing" | | 3 | "was looking" | | 4 | "was still falling" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 106 | | ratio | 0.085 | | matches | | 0 | "He glanced back then — just once — and his face under the streetlight was pale and wet and twisted with something that didn't look like guilt." | | 1 | "Quinn followed between the stalls — tarps snapping in the wind, empty trays, a fox that scattered from a bin — and burst out the far side in time to see him duck down a stairwell beneath a rusted sign she couldn't read in the dark." | | 2 | "The stairs descended into darkness — old tiles, curved walls, a Underground roundel so faded she could barely make out the bar through the circle." | | 3 | "All of it was wrong, and she knew it the way she'd known things in the army — the way she'd known, three years ago, that the warehouse where Morris died was wrong before they ever kicked the door." | | 4 | "Walk back to the car, get signal, request backup, do it by the book — the book she'd been bending for eleven months on a case her DCI had twice told her to drop." | | 5 | "The man who might know — might actually know — what had happened to her partner." | | 6 | "The tiles changed as she descended — Victorian green giving way to something older, grey stone sweating with moisture, carved with symbols she told herself were graffiti." | | 7 | "Beyond it, the old platform stretched away into lamplight — actual gas lamps, hissing softly on iron posts — and between them, stalls." | | 8 | "But Harlow Quinn had spent eighteen years training herself to look at the worst thing first, so she turned her head and let herself see it — the stall selling teeth that were too long, the child-sized figure with grey skin haggling over a bottle, the man at the far end of the platform whose shadow pointed the wrong way." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 616 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.03896103896103896 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.008116883116883116 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 14.06 | | std | 12.35 | | cv | 0.879 | | sampleLengths | | 0 | 17 | | 1 | 23 | | 2 | 5 | | 3 | 14 | | 4 | 8 | | 5 | 19 | | 6 | 14 | | 7 | 10 | | 8 | 21 | | 9 | 13 | | 10 | 20 | | 11 | 17 | | 12 | 16 | | 13 | 4 | | 14 | 46 | | 15 | 10 | | 16 | 6 | | 17 | 5 | | 18 | 27 | | 19 | 4 | | 20 | 19 | | 21 | 2 | | 22 | 25 | | 23 | 15 | | 24 | 21 | | 25 | 5 | | 26 | 8 | | 27 | 3 | | 28 | 23 | | 29 | 46 | | 30 | 3 | | 31 | 18 | | 32 | 4 | | 33 | 7 | | 34 | 25 | | 35 | 14 | | 36 | 29 | | 37 | 3 | | 38 | 39 | | 39 | 4 | | 40 | 3 | | 41 | 10 | | 42 | 5 | | 43 | 14 | | 44 | 4 | | 45 | 1 | | 46 | 15 | | 47 | 5 | | 48 | 2 | | 49 | 27 |
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| 57.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.4339622641509434 | | totalSentences | 106 | | uniqueOpeners | 46 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 89 | | matches | | 0 | "Maybe that was closer to" | | 1 | "Then he was gone again," | | 2 | "Instead he'd gone down." | | 3 | "Then the stairs ended at" | | 4 | "Then she stepped forward, past" |
| | ratio | 0.056 | |
| 94.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 89 | | matches | | 0 | "He recovered without looking back." | | 1 | "They never looked back until" | | 2 | "She'd shouted it four times" | | 3 | "He was quick for a" | | 4 | "she tried, dropping the formality" | | 5 | "He glanced back then —" | | 6 | "It looked like pity." | | 7 | "Her left wrist ached where" | | 8 | "She ran with her jaw" | | 9 | "She was faster than Herrera." | | 10 | "She'd been closing the gap" | | 11 | "She'd assumed he was running" | | 12 | "She reached the stairwell mouth" | | 13 | "She'd ignored it then." | | 14 | "She looked at the display:" | | 15 | "She looked at her phone." | | 16 | "She should call it in." | | 17 | "She didn't know the name" | | 18 | "He'd stopped running." | | 19 | "He stood with his hands" |
| | ratio | 0.315 | |
| 77.98% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 89 | | matches | | 0 | "The rain had been falling" | | 1 | "He recovered without looking back." | | 2 | "They never looked back until" | | 3 | "She'd shouted it four times" | | 4 | "Each time, her voice came" | | 5 | "Nobody stopped for anything in" | | 6 | "That was half the reason" | | 7 | "Herrera splashed through a standing" | | 8 | "He was quick for a" | | 9 | "A former paramedic who'd lost" | | 10 | "Quinn had built her file" | | 11 | "Tonight, something had changed." | | 12 | "Tonight she'd watched him carry" | | 13 | "she tried, dropping the formality" | | 14 | "He glanced back then —" | | 15 | "It looked like pity." | | 16 | "Her left wrist ached where" | | 17 | "She ran with her jaw" | | 18 | "She was faster than Herrera." | | 19 | "She'd been closing the gap" |
| | ratio | 0.764 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 89 | | matches | | 0 | "As if he'd reached sanctuary." | | 1 | "As if the street above" | | 2 | "If they were people." |
| | ratio | 0.034 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 4 | | matches | | 0 | "A former paramedic who'd lost his license for treating patients that didn't exist in any NHS registry." | | 1 | "He glanced back then — just once — and his face under the streetlight was pale and wet and twisted with something that didn't look like guilt." | | 2 | "But Harlow Quinn had spent eighteen years training herself to look at the worst thing first, so she turned her head and let herself see it — the stall selling t…" | | 3 | "Quinn thought of Morris's watch ticking on her wrist, counting out a minute that had already forgotten itself once tonight." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "she breathed (breathe)" |
| | dialogueSentences | 16 | | tagDensity | 0.438 | | leniency | 0.875 | | rawRatio | 0.143 | | effectiveRatio | 0.125 | |